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Estimation Of Dsge Models When The Data Are Persistent
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Book Synopsis Estimation of DSGE models when the data are persistent by : Yuriy Gorodnichenko
Download or read book Estimation of DSGE models when the data are persistent written by Yuriy Gorodnichenko and published by . This book was released on 2009 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Stochastic General Equilibrium (DSGE) models are often solved and estimated under specific assumptions as to whether the exogenous variables are difference or trend stationary. However, even mild departures of the data generating process from these assumptions can severely bias the estimates of the model parameters. This paper proposes new estimators that do not require researchers to take a stand on whether shocks have permanent or transitory effects. These procedures have two key features. First, the same filter is applied to both the data and the model variables. Second, the filtered variables are stationary when evaluated at the true parameter vector. The estimators are approximately normally distributed not only when the shocks are mildly persistent, but also when they have near or exact unit roots. Simulations show that these robust estimators perform well especially when the shocks are highly persistent yet stationary. In such cases, linear detrending and first differencing are shown to yield biased or imprecise estimates.
Book Synopsis Estimating DSGE Models with Unknown Data Persistence by : Gianluca Moretti
Download or read book Estimating DSGE Models with Unknown Data Persistence written by Gianluca Moretti and published by . This book was released on 2010 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Estimating DSGE Models with Long Memory Dynamics by : Gianluca Moretti
Download or read book Estimating DSGE Models with Long Memory Dynamics written by Gianluca Moretti and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent literature claims that key variables such as aggregate productivity and inflation display long memory dynamics. We study the implications of this high degree of persistence on the estimation of Dynamic Stochastic General Equilibrium (DSGE) models. We show that long memory data produce substantial bias in the deep parameter estimates when a standard Kalman Filter-MLE procedure is used. We propose a modification of the Kalman Filter to effectively deal with this problem. The augmented Kalman Filter can consistently estimate the model parameters as well as produce more accurate out-of-sample forecasts compared to the standard Kalman filter.
Book Synopsis Estimation and evaluation of DSGE models : progress and challenges by : Frank Schorfheide
Download or read book Estimation and evaluation of DSGE models : progress and challenges written by Frank Schorfheide and published by . This book was released on 2011 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: Estimated dynamic stochastic equilibrium (DSGE) models are now widely used for empirical research in macroeconomics as well as for quantitative policy analysis and forecasting at central banks around the world. This paper reviews recent advances in the estimation and evaluation of DSGE models, discusses current challenges, and provides avenues for future research
Book Synopsis Online Estimation of DSGE Models by : Michael D. Cai
Download or read book Online Estimation of DSGE Models written by Michael D. Cai and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper illustrates the usefulness of sequential Monte Carlo (SMC) methods in approximating DSGE model posterior distributions. We show how the tempering schedule can be chosen adaptively, document the accuracy and runtime benefits of generalized data tempering for "online" estimation (that is, re-estimating a model as new data become available), and provide examples of multimodal posteriors that are well captured by SMC methods. We then use the online estimation of the DSGE model to compute pseudo-out-of-sample density forecasts and study the sensitivity of the predictive performance to changes in the prior distribution. We find that making priors less informative (compared to the benchmark priors used in the literature) by increasing the prior variance does not lead to a deterioration of forecast accuracy.
Book Synopsis What You Match Does Matter by : Pablo Guerrón-Quintana
Download or read book What You Match Does Matter written by Pablo Guerrón-Quintana and published by . This book was released on 2007 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper explores the effects of using alternative data sets for the estimation of DSGE models. I find that the estimated structural parameters and the model's outcomes are sensitive to the variables used for estimation. Depending on the set of variables the point estimate for habit formation ranges from 0.70 to 0.97. Similarly, the interest-smoothing coefficient in the Taylor rule fluctuates between 0.06 and 0.76. In terms of the model's predictions, if interest rates are excluded during estimation, the estimated structural coefficients are such that the model forecasts a strong deflation following an expansionary monetary expansion. Three ways to assess different observable sets are proposed. Based on these measures, I find that that including the price of investment in the data set delivers the best results.
Book Synopsis Estimation of DSGE Models Under Diffuse Priors and Data-driven Identification Constraints by : Markku Lanne
Download or read book Estimation of DSGE Models Under Diffuse Priors and Data-driven Identification Constraints written by Markku Lanne and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Revisions and DSGE Models by : Ana Beatriz Galvão
Download or read book Data Revisions and DSGE Models written by Ana Beatriz Galvão and published by . This book was released on 2016 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: The typical estimation of DSGE models requires data on a set of macroeconomic aggregates, such as output, consumption and investment, which are subject to data revisions. The conventional approach employs the time series that is currently available for these aggregates for estimation, implying that the last observations are still subject to many rounds of revisions. This paper proposes a release-based approach that uses revised data of all observations to estimate DSGE models, but the model is still helpful for real-time forecasting. This new approach accounts for data uncertainty when predicting future values of macroeconomic variables subject to revisions, thus providing policy-makers and professional forecasters with both backcasts and forecasts. Application of this new approach to a medium-sized DSGE model improves the accuracy of density forecasts, particularly the coverage of predictive intervals, of US real macro variables. The application also shows that the estimated relative importance of business cycle sources varies with data maturity.
Book Synopsis Critically Assessing Estimated DSGE Models by : X. Liu
Download or read book Critically Assessing Estimated DSGE Models written by X. Liu and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Solution and Estimation Methods for DSGE Models by :
Download or read book Solution and Estimation Methods for DSGE Models written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis DSGE Models in Macroeconomics by : Nathan Balke
Download or read book DSGE Models in Macroeconomics written by Nathan Balke and published by Emerald Group Publishing. This book was released on 2012-11-29 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume of Advances in Econometrics contains articles that examine key topics in the modeling and estimation of dynamic stochastic general equilibrium (DSGE) models. Because DSGE models combine micro- and macroeconomic theory with formal econometric modeling and inference, over the past decade they have become an established framework for analy
Book Synopsis Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model by : Mr.Maxym Kryshko
Download or read book Bayesian Dynamic Factor Analysis of a Simple Monetary DSGE Model written by Mr.Maxym Kryshko and published by International Monetary Fund. This book was released on 2011-09-01 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt: When estimating DSGE models, the number of observable economic variables is usually kept small, and it is conveniently assumed that DSGE model variables are perfectly measured by a single data series. Building upon Boivin and Giannoni (2006), we relax these two assumptions and estimate a fairly simple monetary DSGE model on a richer data set. Using post-1983 U.S.data on real output, inflation, nominal interest rates, measures of inverse money velocity, and a large panel of informational series, we compare the data-rich DSGE model with the regular - few observables, perfect measurement - DSGE model in terms of deep parameter estimates, propagation of monetary policy and technology shocks and sources of business cycle fluctuations. We document that the data-rich DSGE model generates a higher implied duration of Calvo price contracts and a lower slope of the New Keynesian Phillips curve. To reduce the computational costs of the likelihood-based estimation, we employed a novel speedup as in Jungbacker and Koopman (2008) and achieved the time savings of 60 percent.
Book Synopsis Forming Priors for DSGE Models and how it Affects the Assessment of Nominal Rigidities by : Marco Del Negro
Download or read book Forming Priors for DSGE Models and how it Affects the Assessment of Nominal Rigidities written by Marco Del Negro and published by . This book was released on 2008 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper discusses prior elicitation for the parameters of dynamic stochastic general equilibrium (DSGE) models, and provides a method for constructing prior distributions for a subset of these parameters from beliefs about the moments of the endogenous variables. The empirical application studies the role of price and wage rigidities in a New Keynesian DSGE model and finds that standard macro time series cannot discriminate among theories that differ in the quantitative importance of nominal frictions.
Book Synopsis Estimating DSGE Models by : Jesús Fernández-Villaverde
Download or read book Estimating DSGE Models written by Jesús Fernández-Villaverde and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: We review the current state of the estimation of DSGE models. After introducing a general framework for dealing with DSGE models, the state-space representation, we discuss how to evaluate moments or the likelihood function implied by such a structure. We discuss, in varying degrees of detail, recent advances in the field, such as the tempered particle filter, approximated Bayesian computation, the Hamiltonian Monte Carlo, variational inference, and machine learning, methods that show much promise, but that have not been fully explored yet by the DSGE community. We conclude by outlining three future challenges for this line of research.
Book Synopsis Quasi-Bayesian Estimation of Time-Varying Volatility in DSGE Models by : Katerina Petrova
Download or read book Quasi-Bayesian Estimation of Time-Varying Volatility in DSGE Models written by Katerina Petrova and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a novel quasi-Bayesian Metropolis-within-Gibbs algorithm that can be used to estimate drifts in the shock volatilities of a linearized dynamic stochastic general equilibrium (DSGE) model. The resulting volatility estimates differ from the existing approaches in two ways. First, the time variation enters non-parametrically, so that our approach ensures consistent estimation in a wide class of processes, thereby eliminating the need to specify the volatility law of motion and alleviating the risk of invalid inference due to mis-specification. Second, the conditional quasi-posterior of the drifting volatilities is available in closed form, which makes inference straightforward and simplifies existing algorithms. We apply our estimation procedure to a standard DSGE model and find that the estimated volatility paths are smoother compared to alternative stochastic volatility estimates. Moreover, we demonstrate that our procedure can deliver statistically significant improvements to the density forecasts of the DSGE model compared to alternative methods.
Book Synopsis Estimation of Continuous-time Linear DSGE Models from Discrete-time Measurements by : Bent Jesper Christensen
Download or read book Estimation of Continuous-time Linear DSGE Models from Discrete-time Measurements written by Bent Jesper Christensen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Non-Stationary Hours in a DSGE Model by : Yongsung Chang
Download or read book Non-Stationary Hours in a DSGE Model written by Yongsung Chang and published by . This book was released on 2019 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: The time series fit of dynamic stochastic general equilibrium (DSGE) models often suffers from restrictions on the long-run dynamics that are at odds with the data. Relaxing these restrictions can close the gap between DSGE models and vector autoregressions. This paper modifies a simple stochastic growth model by incorporating permanent labor supply shocks that can generate a unit root in hours worked. Using Bayesian methods the authors estimate two versions of the DSGE model: the standard specification in which hours worked are stationary and the modified version with permanent labor supply shocks. We find that the data support the latter specification.
